Monitoring of humans energy expenditure during a day is used in devices for medical, healthcare and consumer lifestyle applications.
Known devices for measuring energy expenditure use motion sensors attached to a person's thigh or waist. By analyzing sensor outputs, energy expenditures of e.g. running or walking can be determined. However, such methods have shown to give less accurate measures of energy expenditure for certain activities such as cycling.
EP 1302162 discloses an exercise amount measuring device comprising an acceleration sensor for detecting a body movement of a living body, means for calculating an exercise amount based on a detection signal of the acceleration sensor, and a display section for displaying the calculated exercise amount, said device further comprising: means for calculating an estimated consumption calorie value representing consumption of energy in a prescribed period; and a display section for displaying the calculated estimated consumption calorie value.
Whereas EP 1302162 discloses a device for estimating energy consumption during a prescribed period, it is questionable whether the device is capable of determining the consumed energy of different activities such as cycling with sufficient accuracy. Accordingly, it is an object of the present invention to improve the estimation of energy expenditures of different types of activities.
It should be noted that paper “estimation of activity energy expenditure based on activity classification using multi-site triaxial accelerometry”, Kim D. et Al., Electronics Letters, IEE stevenage, GB, vol. 44, no. 4, 14 Feb. 2008, pages 266-267, XP006030492 ISSN:0013-5194, describes a wireless networked multi-site triaxial accelerometry system to estimate activity energy expenditure during daily life. A feature of the system is the utilization of activity classification based on multi-site acceleration signals. The signal processing and estimation algorithm, uses the integral of absolute values of accelerometer output. These values were then converted to estimate activity energy expenditure using a linear regression equation based on reference data obtained using a standard method. Activity during a given period was automatically classified into two categories, i.e. arm-dominant and leg-dominant activities, according to the ratio of wrist to ankle acceleration signal amplitudes. This ratio was incorporated into the regression analysis as an additional factor.
Further, it should be noted that paper “A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity”, Carlijn V. C. Bouten et al., IEEE transactions on biomedical engineering, IEEE service center, Piscataway, N.J., US, vol. 44, no. 3, 1 Mar. 1997, XP011006346 ISSN:0018-9294, describes the development of a triaxial accelerometer (TA) and a portable data processing unit for the assessment of daily physical activity. The TA is composed of three orthogonally mounted uniaxial piezoresistive accelerometers and can be used to register accelerations covering the amplitude and frequency ranges of human body acceleration. The data unit enables the on-line processing of accelerometer output to an estimator of physical activity over eight-day periods. Further, it should be noted that WO 2004/032715 (Bodymedia Inc.) 22 Apr. 2004, describes a method and apparatus for measuring a state parameter of an individual using signals based on one or more sensors. In one embodiment, a first set of signals is used in a first function to determine how a second set of signals is used in one or more second functions to predict the state parameter. In another embodiment, first and second functions are used where the state parameter or an indicator of the state parameter may be obtained from a relationship between the first function and the second function. The state parameter may, for example, include calories consumed or calories burned by the individual.